Richmond, VA

Developer Jobs in Richmond, VA

5 jobs found

Include remote jobs

10d ago

Lead Machine Learning Engineer (Manager IC)

Capital One Richmond, VA

Richmond, VA

10d ago

Full time Manager Agentic Ai Ai Ml

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Job Description

Lead Machine Learning Engineer (Manager IC) in Capital One's Risk Tech group, onsite in Richmond, VA, focusing on designing, deploying, and maintaining AI/ML powered risk management solutions and shaping the long term AI roadmap through cross-functional collaboration.

Responsibilities

Partner with a cross functional team of engineers, data scientists, product managers, and designers to deliver AI driven products that transform how associates operate and deliver value to customers.
Architect, build, validate, deploy, and maintain AI software components driven by ML models, including model evaluation, experimentation, large language model inference, similarity search, guardrails, governance, observability, and agentic AI.
Fine tune, develop, and evaluate machine learning and foundation models.
Join an Agile, cross functional team to create and enhance software that leverages cutting edge AI and ML capabilities.
Provide thought leadership and technical direction for Capital One's long term AI systems roadmap.
Utilize a broad stack of open source and SaaS AI technologies.
Guide ML infrastructure decisions based on modeling techniques and related considerations.
Retrain, maintain, and monitor production models.
Build optimized data pipelines to feed ML models.
Ensure code quality and security, govern models from a risk perspective, and adhere to Responsible and Explainable AI best practices.

Requirements

Bachelor’s Degree
Minimum 6 years designing and building data intensive solutions using distributed computing (internship experience does not apply)
Minimum 4 years programming in Python, Scala, or Java
Minimum 2 years building, scaling, and optimizing ML systems

Technologies

Python
Scala
Java
scikit-learn
PyTorch
Dask
Spark
TensorFlow
AWS Bedrock
Google Cloud
Azure
Retrieval Augmented Generation (RAG)

Benefits

Performance-based incentive compensation (cash bonuses and long-term incentives).
Health, financial and other benefits that support total well-being.

The ideal candidate

You love to build systems, take pride in the quality of your work, and are motivated by solving problems that can change banking for good.
You are a skilled communicator, able to explain complex technical concepts to non-technical partners across the business, sometimes in front of large audiences.
You stay current with the latest research and can read scientific publications to judiciously apply novel techniques in production.
You adapt quickly, bring clarity to big, undefined problems, ask questions, and dig deep to uncover root causes, articulating findings concisely; you share new ideas even when unproven.
You are deeply technical with a strong foundation in engineering and mathematics, leveraging hardware, software, and AI knowledge to identify optimization opportunities others miss.
You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unclear.
You maintain a passion for AI research and AI systems, applying novel techniques in production with care.

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10d ago

Lead Machine Learning Engineer

Capital One Richmond, VA

Richmond, VA

10d ago

Full time Agentic Ai Ai Ml Artificial Intelligence

Apply Now

Job Description

Lead Machine Learning Engineer role at Capital One in Risk Tech focuses on designing, deploying, and maintaining AI and ML systems while delivering AI powered products with an emphasis on responsible and explainable AI.

Responsibilities

Collaborate with engineers, data scientists, product managers, and designers to deliver AI powered solutions that improve associates' workflows and customer value.
Design, develop, test, deploy, and support AI software components using machine learning models, including model evaluation, experimentation, large language model inference, similarity search, guardrails, governance, observability, and agentic AI.
Fine tune, develop, and evaluate machine learning and foundational models.
Work within a cross functional Agile team to build and enhance software that leverages advanced AI and ML capabilities.
Contribute thought leadership and technical vision to the long term AI roadmap at Capital One.
Leverage a broad mix of Open Source and SaaS AI technologies.
Inform ML infrastructure decisions based on an understanding of modeling techniques and associated challenges.
Retrain, maintain, and monitor models in production environments.
Build optimized data pipelines to feed ML models.
Ensure code quality reduces vulnerabilities, maintain model governance from a risk perspective, and follow Responsible and Explainable AI practices.

Requirements

Bachelor’s Degree
At least 6 years of experience designing and building data intensive solutions using distributed computing (Internship experience does not apply)
At least 4 years of experience programming with Python, Scala, or Java
At least 2 years of experience building, scaling, and optimizing ML systems

Technologies

Python
Scala
Java
scikit-learn
PyTorch
Dask
Spark
TensorFlow
AWS Bedrock
Google Cloud
Azure
Retrieval Augmented Generation (RAG)

Benefits

Health benefits
Financial benefits
Other benefits
Performance-based incentive compensation (cash bonus(es) and/or long term incentives)

The ideal candidate

You love building systems, take pride in quality, and share a commitment to doing the right thing while tackling problems that can transform banking.
You are a strong communicator who can explain complex technical concepts to non technical partners across the business, including presentations to large audiences.
You stay current with AI research and can interpret scientific publications to apply novel techniques in production.
You adapt quickly, bring clarity to large, undefined problems, ask questions, and dig deep to uncover root causes, articulating findings concisely; you are willing to share new ideas even when unproven.
You are deeply technical with a solid foundation in engineering and mathematics, and you can spot optimization opportunities across hardware, software, and AI.
You are a resilient trailblazer who can forge new paths to meet business goals when the path is unclear.
You maintain a strong appetite for staying current with AI research and systems, applying novel techniques in production in a prudent manner.

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10d ago

Lead Machine Learning Engineer (Manager IC)

Capital One Richmond, VA

Richmond, VA

10d ago

$179k - $205k/yr Full time Manager Ai Ml Artificial Intelligence

Apply Now

Job Description

Capital One Risk Tech is seeking a Lead Machine Learning Engineer who will design, deploy, and maintain AI components and infrastructure that power risk management and AI-enabled products. This onsite role in Richmond, VA blends hands-on engineering leadership with strategic vision to advance Capital One's AI systems and risk controls.

Location

Richmond, VA (onsite)

Compensation

USD 179,400 - 204,700 per year

Responsibilities

Collaborate with a cross-functional team of engineers, data scientists, product managers, and designers to deliver AI-powered products that transform how associates work and provide value to customers.
Design, develop, test, deploy, and support AI software components using machine learning models, including model evaluation and experimentation, large language model inference, similarity search, guardrails, governance, observability, and agentic AI.
Fine-tune, develop, and evaluate machine learning and foundation models.
Work within an Agile, cross-functional team to create and enhance software that leverages state-of-the-art AI and ML capabilities.
Provide thought leadership and technical vision for the long-term roadmap of pioneering AI systems at Capital One.
Utilize a broad stack of Open Source and SaaS AI technologies.
Guide ML infrastructure decisions based on an understanding of ML modeling techniques and related issues.
Retrain, maintain, and monitor models in production.
Build optimized data pipelines to feed ML models.
Ensure code is well-managed to reduce vulnerabilities, keep models well-governed from a risk perspective, and follow responsible and explainable AI practices.

Requirements

Bachelor’s Degree
Minimum of six years designing and building data-intensive solutions on distributed computing platforms (internships excluded)
Minimum of four years programming in Python, Scala, or Java
Minimum of two years building, scaling, and optimizing ML systems

Technologies

Python
Scala
Java
scikit-learn
PyTorch
Dask
Spark
TensorFlow
AWS Bedrock
Google Cloud
Azure

Benefits

Health, financial and other benefits that support your total well-being
Performance-based incentive compensation (cash bonuses and/or long term incentives)

The ideal candidate

You love to build systems, take pride in the quality of your work, and aim to contribute to banking improvements that matter.
You are a strong communicator who can explain complex technical concepts to non-technical partners across the business, including presentations to large audiences.
You stay current with AI research and can interpret scientific publications to judiciously apply novel techniques in production.
You adapt quickly and bring clarity to big, undefined problems, asking probing questions and articulating findings concisely, with the courage to propose new ideas even if unproven.
You are deeply technical, with a solid foundation in engineering and mathematics, and an ability to see and exploit optimization opportunities across hardware, software, and AI.
You are a resilient trailblazer who can forge new paths to achieve business goals when the route is uncertain.
You maintain a passion for the latest AI research and systems, applying novel techniques in production with careful consideration.

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18d ago

Managed Services - Senior Data Engineer - Senior Manager

PRICE WATERHOUSE COOPERS Richmond, VA

Richmond, VA

18d ago

$124k - $280k/yr Full time Manager Senior Analytics

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Job Description

A senior data engineering leadership role with PwC, onsite in Richmond, VA, offering a salary range of USD 124,000 to 280,000 per year and requiring a bachelor’s degree with at least six years of experience.

Responsibilities

Develop innovative solutions to optimize client business performance and strengthen competitive advantage, including roadmap development.
Apply advanced analytics to support client operations and strategic goals using AWS data engineering and Redshift.
Design, build, and maintain data pipelines and architectures to support business intelligence efforts, leveraging DataStage and ETL processes.
Implement data visualization capabilities to provide actionable insights and improve client outcomes with SQL Server and DB2.
Collaborate with stakeholders to identify data challenges and opportunities, aligning work with managed services standards and SLAs.
Coach and motivate teams to solve complex problems and deliver high quality results.
Apply systems thinking to identify underlying problems and opportunities within client projects, including workload orchestration and scheduling.
Validate outcomes with clients and act on feedback to refine solutions, tracking CSAT and performance tuning metrics.
Lead teams through ambiguous and challenging situations with composure and sound judgment.

Requirements

Bachelor's degree
At least 6 years of experience

Technologies

AWS
Redshift
DataStage
SQL Server
DB2
Python
Java
QlikView
Oracle BI

Benefits

Medical
Dental
Vision
401k
Holiday pay
Vacation
Personal and family sick leave
Annual discretionary bonus

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28d ago

Senior Lead Machine Learning Engineer

Capital One Richmond, VA

Richmond, VA

28d ago

$209k - $239k/yr Full time Azure Ml Cloud Operations Data Engineer

Apply Now

Job Description

Capital One is seeking a Senior Lead Machine Learning Engineer to mature machine learning applications from concept to production at scale. In this capacity, you will shape the architecture, design, and deployment strategy within Agile teams, prioritizing reliability, governance, and performance. This on-site role is based in Richmond, Virginia, with a salary in the range of USD 209,000 to 238,500 per year.

Responsibilities

Design and deliver ML models and components that address real world business problems, collaborating with Product and Data Science teams.
Make informed ML infrastructure decisions by applying modeling techniques and addressing issues such as model choice, data, feature selection, training, hyperparameters, dimensionality, bias/variance, and validation.
Tackle complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment.
Collaborate within a cross-functional Agile team to build and enhance software powering advanced big data and ML applications.
Retrain, maintain, and monitor models in production.
Utilize or build cloud-based architectures, technologies, and platforms to deliver optimized ML models at scale.
Construct optimized data pipelines to feed ML models.
Apply continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code.
Ensure code quality, governance, risk management, and adherence to Responsible and Explainable AI practices.
Demonstrate proficiency in Python, Scala, or Java.

Requirements

Bachelor's Degree
At least 8 years designing and building data-intensive solutions using distributed computing (Internship experience does not apply)
At least 4 years programming with Python, Scala, or Java
At least 3 years building, scaling, and optimizing ML systems
At least 2 years leading teams developing ML solutions

Technologies

Python
Scala
Java
scikit-learn
PyTorch
Dask
Spark
TensorFlow
AWS
Azure
Google Cloud Platform

Benefits

Health benefits
Financial benefits
Performance-based incentives (cash bonuses and long-term incentives)

Preferred Qualifications

Master's or doctoral degree in computer science, electrical engineering, mathematics, or a related field
Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform
4+ years of experience with industry-recognized ML frameworks such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow
3+ years of experience developing performant, resilient, and maintainable code
3+ years of experience with data gathering and preparation for ML models
3+ years of people management experience
ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents
3+ years building production-ready data pipelines that feed ML models
Ability to communicate complex technical concepts clearly to a variety of audiences

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Developer Jobs in Richmond, VA

Lead Machine Learning Engineer (Manager IC)

Lead Machine Learning Engineer

Lead Machine Learning Engineer (Manager IC)

Managed Services - Senior Data Engineer - Senior Manager

Senior Lead Machine Learning Engineer

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